10/09/2026 updated
100 % available
Senior AI/ML Engineer | LLM Applications | RAG Systems | Python Backend
Lagos, Nigeria
Worldwide
B.Tech Physics/Electronics, Federal University of Technology, MinnaAbout me
Senior AI/ML Engineer building production AI agents, RAG systems, and Python/FastAPI backends. I specialize in LLM integration, workflow automation, secure APIs, and AWS/Azure deployment. Experienced in recruitment AI, KYC/AML, document intelligence, and CRM automation.
LLMAzure Kubernetes ServiceApplication Programming Interfaces (APIs)Microsoft AzurePython (Programming Language)PostgreSQLMachine LearningMessaging Application Programming InterfacePrometheusAzure Machine LearningSQLAlchemyFeature EngineeringPyTorchFlaskPrompt Engineering
AI & LLM Engineering
Expertise in building and shipping production LLM applications, AI agents, RAG systems, and evaluation workflows using LangChain, LlamaIndex, OpenAI API, Claude API, Azure OpenAI, Tool Calling, Agent Orchestration, Prompt Engineering, Structured Outputs, Guardrails, Embeddings, and Semantic Search.
Backend Engineering
Strong foundation in Python backend development with FastAPI, Flask, Pydantic, SQLAlchemy, Async Processing, REST APIs, OAuth2/OIDC, JWT, Webhooks, and Microservices for scalable, multi-tenant production platforms.
AI Evaluation
Proficiency in LLM Evaluation, Agent Evaluation, Model Evaluation, Rubric-Based Evaluation, Error Analysis, Output Validation, Prompt Testing, and Retrieval Evaluation to ensure quality, reliability, and inference cost efficiency.
Data & Retrieval
Hands-on experience with PostgreSQL, pgvector, Redis, Qdrant, SQL, Pandas, NumPy, Scikit-learn, and Vector Databases for data storage, retrieval, and machine learning pipelines.
Cloud & DevOps
Practical knowledge of AWS, Azure, Azure AI Foundry, Azure App Service, Docker, Docker Compose, Kubernetes, GitHub Actions, and CI/CD for deploying and managing production AI systems.
Machine Learning & Data Science
Experience building predictive machine-learning systems using Python, Pandas, NumPy, Scikit-learn, and NLP, including feature engineering, model validation, error analysis, and iterative experimentation.
Identity Verification & KYC Systems
Development of production identity-verification platforms integrating OCR, Azure Document Intelligence, face/liveness verification, compliance screening, and AI-assisted decision workflows.
Workflow Automation & Prompt Engineering
Design and implementation of 200+ LLM prompt workflows for document classification, structured extraction, and downstream automation, achieving high accuracy through validation pipelines.
IT & Digital Operations Management
Leadership of IT operations, digital transformation, business automation, and data initiatives, including Python and Pandas automation for multi-source data processing, validation, reporting, and customer-retention analytics.
Expertise in building and shipping production LLM applications, AI agents, RAG systems, and evaluation workflows using LangChain, LlamaIndex, OpenAI API, Claude API, Azure OpenAI, Tool Calling, Agent Orchestration, Prompt Engineering, Structured Outputs, Guardrails, Embeddings, and Semantic Search.
Backend Engineering
Strong foundation in Python backend development with FastAPI, Flask, Pydantic, SQLAlchemy, Async Processing, REST APIs, OAuth2/OIDC, JWT, Webhooks, and Microservices for scalable, multi-tenant production platforms.
AI Evaluation
Proficiency in LLM Evaluation, Agent Evaluation, Model Evaluation, Rubric-Based Evaluation, Error Analysis, Output Validation, Prompt Testing, and Retrieval Evaluation to ensure quality, reliability, and inference cost efficiency.
Data & Retrieval
Hands-on experience with PostgreSQL, pgvector, Redis, Qdrant, SQL, Pandas, NumPy, Scikit-learn, and Vector Databases for data storage, retrieval, and machine learning pipelines.
Cloud & DevOps
Practical knowledge of AWS, Azure, Azure AI Foundry, Azure App Service, Docker, Docker Compose, Kubernetes, GitHub Actions, and CI/CD for deploying and managing production AI systems.
Machine Learning & Data Science
Experience building predictive machine-learning systems using Python, Pandas, NumPy, Scikit-learn, and NLP, including feature engineering, model validation, error analysis, and iterative experimentation.
Identity Verification & KYC Systems
Development of production identity-verification platforms integrating OCR, Azure Document Intelligence, face/liveness verification, compliance screening, and AI-assisted decision workflows.
Workflow Automation & Prompt Engineering
Design and implementation of 200+ LLM prompt workflows for document classification, structured extraction, and downstream automation, achieving high accuracy through validation pipelines.
IT & Digital Operations Management
Leadership of IT operations, digital transformation, business automation, and data initiatives, including Python and Pandas automation for multi-source data processing, validation, reporting, and customer-retention analytics.
Experience
Professional experience5 - 10 years
Freelancer since2017
Languages
EnglishNative speaker
Project history
Architect and own production AI platforms spanning LLM agents, RAG, semantic retrieval, evaluation systems, and multi-tenant Python services using FastAPI, PostgreSQL/pgvector, Redis, OpenAI, Claude, Azure AI, and Docker. Led development of AIRA, an enterprise AI recruiting platform combining semantic candidate retrieval, automated resume analysis, structured candidate scoring, PII-blind evaluation, and AI-assisted hiring workflows. Designed stateful agent architecture with scoped tool permissions, deterministic transitions, Pydantic contracts, structured outputs, validation layers, and prompt guardrails. Engineered multi-tenant backend services with API-key authentication, OAuth2/JWT, asynchronous processing, Redis caching, rate limiting, webhook delivery, retry logic, and idempotency controls. Built hybrid evaluation pipelines combining deterministic rules, embeddings, semantic retrieval, and LLM reasoning.
Designed 200+ LLM prompt workflows for mortgage-document classification, document understanding, structured extraction, and downstream automation. Built RAG-based document retrieval and contextual reasoning workflows with LlamaIndex, achieving approximately 95% structured extraction accuracy through validation pipelines.
Built predictive machine-learning systems using Python, Pandas, NumPy, Scikit-learn, and NLP, including models reaching approximately 89% predictive accuracy. Developed automated data and ML workflows supporting experimentation, validation, reporting, and business decision-making. Conducted feature engineering, model validation, error analysis, and iterative experimentation to improve model performance and reliability.